Abstract: A method for predicting a failure state of an automated analyzer for analyzing a biological sample is disclosed. The method includes obtaining a prediction algorithm for predicting a failure state of an automated analyzer. The prediction algorithm is configured to predict a failure state of the automated analyzer based on calibration data and/or quality control data generated by an automated analyzer. The method also includes obtaining calibration data and/or quality control data of the automated analyzer and processing the calibration data and/or quality control data by using the prediction algorithm to predict a failure state of the automated analyzer.

Abstract: The system includes a processor configured for receiving biomedical documents including an identifier of the target and/or of the disease; specifying an offset time the offset time indicating a time interval ahead of the performing of the prediction; specifying a time window ending at the begin of the offset time; extracting a plurality of features selectively from the ones of the received documents published during the time window; providing a classifier having been trained on training features extracted from biomedical training documents published within a training time window ending at the begin of the offset time ahead of a moment the outcome of one or more training studies on training target-disease-pairs was disclosed; executing the classifier, thereby providing the extracted features as input; and outputting a classification result indicating whether the drug directed at the target can be used to treat the disease.